Association Between Wildfire-Specific Particulate Matter Exposure and Cardiovascular Disease
- saeed, rasha
- Advisor(s): Wu, Jun JW
Abstract
ABSTRACT OF THE THESIS
Association Between Wildfire-Specific Particulate Matter Exposure and Cardiovascular Disease. by Rasha A. M. Saeed Master of Science in Environmental Health University of California, Irvine, 2025 Professor Jun Wu, Chair
Introduction: Wildfire-specific particulate matter 2.5 (PM2.5) refers to particles with an aerodynamic diameter of 2.5 micrometers or less, originating from wildfires. These particles can penetrate systemic circulation, reaching critical organs such as the heart and brain, and contributing to severe adverse health outcomes. While some studies have examined the short-term effects of PM2.5 exposure on cardiovascular disease, they have primarily focused on wildfire-specific PM2.5 at lag day 0-3 (lag day 0 is the day of the exposure, lag day 1 is one day after the exposure and so forth), lacking smoke wave effects. A more detailed analysis is needed to investigate wildfire-specific PM2.5 impacts, particularly during smoke waves, with a focus on lag 0-7 and cumulative lags 0-3 and 0-7, to achieve a more comprehensive understanding of its effects. This study evaluated not only the lag effects (individual lag day 0 to lag day 7, cumulative lag days 0-3 and 0-7) of wildfire specific PM2.5 concentrations but also the role of smoke waves, which reflect a time period of higher smoke concentrations and extended durations of exposure during wildfire events. This approach provides deeper insight into the association between wildfire-specific PM2.5 exposure and cardiovascular disease-related emergency room visits. Methods: This study is a time series analysis that examined the relationship between wildfire-specific PM2.5 exposure and cardiovascular disease outcomes by analyzing emergency department visit data across zip codes in the State of California for the years 2017, 2018, and 2020 to heightened wildfire activity, as those three years experienced significant recent wildfire events, whereas 2019 had comparatively fewer wildfires. Daily PM2.5 concentrations were evaluated alongside daily emergency department visit records. Generalized Estimating Equations (GEE) and negative binomial regression models were utilized, with PM2.5 as the primary exposure variable and cardiovascular disease as the outcome. In addition to treating wildfire-specific PM2.5 as a continuous variable for daily exposure with a lag time of 0-7 days, the study also explored smoke waves that captured the episodes with high wildfire smoke, controlling for demographic, meteorological, and temporal covariates. Statistical analyses were performed using SAS 9.4 (SAS Institute Inc.). Results: Primary analysis revealed a significant positive association between wildfire-specific PM2.5 exposure and overall cardiovascular disease, with relative risks ranging from 1.006 to 1.015 per 10 units of wildfire PM2.5 across all lag periods, The strongest association was observed with cumulative exposure over the lag 0-7 days. Additionally, we identified a significant positive association between the increased intensity and duration of smoke waves (SW) from SW4 to SW9 and the outcomes, ranging from 1.025 to 1.052 per 10-unit increase in wildfire PM2.5, with a noticeable upward trend peaking at SW9. For disease-specific outcomes, a consistent significant positive relationship was identified for cerebrovascular events, including stroke and ischemic stroke, across lag periods 0, 0-3, and 0-7, with relative risks ranging from 1.016 to 1.029 per 10 units of wildfire PM2.5. Notably, the association was more pronounced with older individuals. Conclusion: Elevated levels of wildfire specific PM2.5 exposure were associated with increased emergency department visits for cardiovascular disease in California, with the effect being more pronounced among older age groups. The risk intensified with higher PM2.5 concentrations and prolonged smoke wave durations with highest at SW9 and showing a stronger impact at later lag times (lag 0-7) and cumulative lags (0-3 and 0-7).